Most prior semantic segmentation methods have been developed for day-tim...
Visible-Infrared person Re-IDentification (VI-ReID) is a challenging
cro...
To serve the intricate and varied demands of image editing, precise and
...
With the end of Moore's Law, there is a growing demand for rapid
archite...
Backpropagation algorithm has been widely used as a mainstream learning
...
Collaborative perception is essential to address occlusion and sensor fa...
In unsupervised domain adaptation (UDA), directly adapting from the sour...
Adversarial learning has achieved remarkable performances for unsupervis...
Image semantic segmentation aims at the pixel-level classification of im...
Compared with traditional task-irrelevant downsampling methods, task-ori...
In this paper, a novel approach via embedded tensor manifold regularizat...
Semantic segmentation methods can not directly identify abnormal objects...
Differentiable solvers for the linear assignment problem (LAP) have attr...
Unsupervised person re-identification (ReID) is a challenging task witho...
The RGB-infrared cross-modality person re-identification (ReID) task aim...
Visible-infrared cross-modality person re-identification is a challengin...
In recent years, powered by the learned discriminative representation vi...
Multi-Label Image Classification (MLIC) aims to predict a set of labels ...
Recently, the advancement of 3D point clouds in deep learning has attrac...
In the past few decades, to reduce the risk of X-ray in computed tomogra...
Blind modulation classification is an important step to implement cognit...
In this paper, we propose intelligent reflecting surfaces (IRS) assisted...
Partial Label Learning (PLL) aims to learn from the data where each trai...
Person re-identification (Re-ID) across multiple datasets is a challengi...
According to a report online, more than 200 million unique users search ...
In this paper we explore a class of belief update operators, in which th...